{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading\n",
    "\n",
    "Let's load an existing index (that was created with clip index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"]=\"\"\n",
    "from clip_retrieval.clip_back import load_clip_indices, KnnService"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading clip...\n",
      "loading metadata...\n",
      "loading indices...\n"
     ]
    }
   ],
   "source": [
    "columns = [\"url\", \"caption\"]\n",
    "indices_loaded, indices, device, model, preprocess, mclip_model = load_clip_indices(\"/home/rom1504/indices_paths.json\", True, True, columns, False)\n",
    "knn_service = KnnService(indices_loaded=indices_loaded, device=device, model=model, preprocess=preprocess, columns_to_return=columns, metadata_is_ordered_by_ivf=False, mclip_model=mclip_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Doing a query\n",
    "\n",
    "Let's extract a subset of the dataset composed mostly of watermarked images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = knn_service.query(text_input=\"watermark\", modality=\"image\", indice_name=\"laion_400m\", num_images=1000, num_result_ids=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "url_captions = pd.DataFrame([(e['url'], e['caption']) for e in results], columns=[\"url\", \"caption\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>url</th>\n",
       "      <th>caption</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>https://static2.bigstockphoto.com/thumbs/7/8/3...</td>\n",
       "      <td>Milch spritzt Sammlung, isolated on white back...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>https://t2.ftcdn.net/jpg/00/62/03/77/400_F_620...</td>\n",
       "      <td>Abstract background</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>https://as2.ftcdn.net/jpg/00/57/88/83/500_F_57...</td>\n",
       "      <td>Spoed Foto op Canvas Abstract wave Abstract pa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://image.shutterstock.com/image-photo/sto...</td>\n",
       "      <td>Marine pattern with stylized blue waves. Cosme...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://thumb7.shutterstock.com/image-photo/st...</td>\n",
       "      <td>water background - stock photo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>https://t1.ftcdn.net/jpg/00/54/99/42/400_F_549...</td>\n",
       "      <td>Abstract business background</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>https://img3.stockfresh.com/files/sstk/200/550...</td>\n",
       "      <td>Brickwall as Background for Product Placement ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>https://thumb1.shutterstock.com/image-photo/st...</td>\n",
       "      <td>motorboat and nature - stock vector</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>https://thumb1.shutterstock.com/image-photo/st...</td>\n",
       "      <td>Molecular structure scientific vertical backgr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>https://thumb9.shutterstock.com/image-photo/st...</td>\n",
       "      <td>Connections raster icon. This flat rounded squ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   url  \\\n",
       "0    https://static2.bigstockphoto.com/thumbs/7/8/3...   \n",
       "1    https://t2.ftcdn.net/jpg/00/62/03/77/400_F_620...   \n",
       "2    https://as2.ftcdn.net/jpg/00/57/88/83/500_F_57...   \n",
       "3    https://image.shutterstock.com/image-photo/sto...   \n",
       "4    https://thumb7.shutterstock.com/image-photo/st...   \n",
       "..                                                 ...   \n",
       "995  https://t1.ftcdn.net/jpg/00/54/99/42/400_F_549...   \n",
       "996  https://img3.stockfresh.com/files/sstk/200/550...   \n",
       "997  https://thumb1.shutterstock.com/image-photo/st...   \n",
       "998  https://thumb1.shutterstock.com/image-photo/st...   \n",
       "999  https://thumb9.shutterstock.com/image-photo/st...   \n",
       "\n",
       "                                               caption  \n",
       "0    Milch spritzt Sammlung, isolated on white back...  \n",
       "1                                  Abstract background  \n",
       "2    Spoed Foto op Canvas Abstract wave Abstract pa...  \n",
       "3    Marine pattern with stylized blue waves. Cosme...  \n",
       "4                       water background - stock photo  \n",
       "..                                                 ...  \n",
       "995                       Abstract business background  \n",
       "996  Brickwall as Background for Product Placement ...  \n",
       "997                motorboat and nature - stock vector  \n",
       "998  Molecular structure scientific vertical backgr...  \n",
       "999  Connections raster icon. This flat rounded squ...  \n",
       "\n",
       "[1000 rows x 2 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url_captions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_captions.to_parquet(\"/tmp/mysubset.parquet\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downloading\n",
    "\n",
    "Finally let's download this subset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading file number 1 of 1 called /tmp/mysubset.parquet\n",
      "  0%|                                                     | 0/1 [00:00<?, ?it/s]success=1.00 failed download=0.00 failed resize=0.00\n",
      "100%|█████████████████████████████████████████████| 1/1 [00:08<00:00,  8.00s/it]\n"
     ]
    }
   ],
   "source": [
    "!img2dataset --input_format=parquet --url_list=/tmp/mysubset.parquet --output_folder=/tmp/myoutput --processes_count=16 --thread_count=64 --output_format=files --url_col=\"url\" --caption_col=\"caption\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/tmp/myoutput/00000.parquet\n",
      "\n",
      "/tmp/myoutput/00000:\n",
      "0000.jpg   0143.jpg   0286.jpg\t 0429.jpg   0572.jpg   0715.jpg   0858.jpg\n",
      "0000.json  0143.json  0286.json  0429.json  0572.json  0715.json  0858.json\n",
      "0000.txt   0143.txt   0286.txt\t 0429.txt   0572.txt   0715.txt   0858.txt\n",
      "0001.jpg   0144.jpg   0287.jpg\t 0430.jpg   0573.jpg   0716.jpg   0859.jpg\n",
      "0001.json  0144.json  0287.json  0430.json  0573.json  0716.json  0859.json\n",
      "0001.txt   0144.txt   0287.txt\t 0430.txt   0573.txt   0716.txt   0859.txt\n",
      "0002.jpg   0145.jpg   0288.jpg\t 0431.jpg   0574.jpg   0717.jpg   0860.jpg\n",
      "0002.json  0145.json  0288.json  0431.json  0574.json  0717.json  0860.json\n",
      "0002.txt   0145.txt   0288.txt\t 0431.txt   0574.txt   0717.txt   0860.txt\n",
      "0003.jpg   0146.jpg   0289.jpg\t 0432.jpg   0575.jpg   0718.jpg   0861.jpg\n",
      "0003.json  0146.json  0289.json  0432.json  0575.json  0718.json  0861.json\n",
      "0003.txt   0146.txt   0289.txt\t 0432.txt   0575.txt   0718.txt   0861.txt\n",
      "0004.jpg   0147.jpg   0290.jpg\t 0433.jpg   0576.jpg   0719.jpg   0862.jpg\n",
      "0004.json  0147.json  0290.json  0433.json  0576.json  0719.json  0862.json\n",
      "0004.txt   0147.txt   0290.txt\t 0433.txt   0576.txt   0719.txt   0862.txt\n",
      "0005.jpg   0148.jpg   0291.jpg\t 0434.jpg   0577.jpg   0720.jpg   0863.jpg\n",
      "0005.json  0148.json  0291.json  0434.json  0577.json  0720.json  0863.json\n",
      "0005.txt   0148.txt   0291.txt\t 0434.txt   0577.txt   0720.txt   0863.txt\n",
      "0006.jpg   0149.jpg   0292.jpg\t 0435.jpg   0578.jpg   0721.jpg   0864.jpg\n",
      "0006.json  0149.json  0292.json  0435.json  0578.json  0721.json  0864.json\n",
      "0006.txt   0149.txt   0292.txt\t 0435.txt   0578.txt   0721.txt   0864.txt\n",
      "0007.jpg   0150.jpg   0293.jpg\t 0436.jpg   0579.jpg   0722.jpg   0865.jpg\n",
      "0007.json  0150.json  0293.json  0436.json  0579.json  0722.json  0865.json\n",
      "0007.txt   0150.txt   0293.txt\t 0436.txt   0579.txt   0722.txt   0865.txt\n",
      "0008.jpg   0151.jpg   0294.jpg\t 0437.jpg   0580.jpg   0723.jpg   0866.jpg\n",
      "0008.json  0151.json  0294.json  0437.json  0580.json  0723.json  0866.json\n",
      "0008.txt   0151.txt   0294.txt\t 0437.txt   0580.txt   0723.txt   0866.txt\n",
      "0009.jpg   0152.jpg   0295.jpg\t 0438.jpg   0581.jpg   0724.jpg   0867.jpg\n",
      "0009.json  0152.json  0295.json  0438.json  0581.json  0724.json  0867.json\n",
      "0009.txt   0152.txt   0295.txt\t 0438.txt   0581.txt   0724.txt   0867.txt\n",
      "0010.jpg   0153.jpg   0296.jpg\t 0439.jpg   0582.jpg   0725.jpg   0868.jpg\n",
      "0010.json  0153.json  0296.json  0439.json  0582.json  0725.json  0868.json\n",
      "0010.txt   0153.txt   0296.txt\t 0439.txt   0582.txt   0725.txt   0868.txt\n",
      "0011.jpg   0154.jpg   0297.jpg\t 0440.jpg   0583.jpg   0726.jpg   0869.jpg\n",
      "0011.json  0154.json  0297.json  0440.json  0583.json  0726.json  0869.json\n",
      "0011.txt   0154.txt   0297.txt\t 0440.txt   0583.txt   0726.txt   0869.txt\n",
      "0012.jpg   0155.jpg   0298.jpg\t 0441.jpg   0584.jpg   0727.jpg   0870.jpg\n",
      "0012.json  0155.json  0298.json  0441.json  0584.json  0727.json  0870.json\n",
      "0012.txt   0155.txt   0298.txt\t 0441.txt   0584.txt   0727.txt   0870.txt\n",
      "0013.jpg   0156.jpg   0299.jpg\t 0442.jpg   0585.jpg   0728.jpg   0871.jpg\n",
      "0013.json  0156.json  0299.json  0442.json  0585.json  0728.json  0871.json\n",
      "0013.txt   0156.txt   0299.txt\t 0442.txt   0585.txt   0728.txt   0871.txt\n",
      "0014.jpg   0157.jpg   0300.jpg\t 0443.jpg   0586.jpg   0729.jpg   0872.jpg\n",
      "0014.json  0157.json  0300.json  0443.json  0586.json  0729.json  0872.json\n",
      "0014.txt   0157.txt   0300.txt\t 0443.txt   0586.txt   0729.txt   0872.txt\n",
      "0015.jpg   0158.jpg   0301.jpg\t 0444.jpg   0587.jpg   0730.jpg   0873.jpg\n",
      "0015.json  0158.json  0301.json  0444.json  0587.json  0730.json  0873.json\n",
      "0015.txt   0158.txt   0301.txt\t 0444.txt   0587.txt   0730.txt   0873.txt\n",
      "0016.jpg   0159.jpg   0302.jpg\t 0445.jpg   0588.jpg   0731.jpg   0874.jpg\n",
      "0016.json  0159.json  0302.json  0445.json  0588.json  0731.json  0874.json\n",
      "0016.txt   0159.txt   0302.txt\t 0445.txt   0588.txt   0731.txt   0874.txt\n",
      "0017.jpg   0160.jpg   0303.jpg\t 0446.jpg   0589.jpg   0732.jpg   0875.jpg\n",
      "0017.json  0160.json  0303.json  0446.json  0589.json  0732.json  0875.json\n",
      "0017.txt   0160.txt   0303.txt\t 0446.txt   0589.txt   0732.txt   0875.txt\n",
      "0018.jpg   0161.jpg   0304.jpg\t 0447.jpg   0590.jpg   0733.jpg   0876.jpg\n",
      "0018.json  0161.json  0304.json  0447.json  0590.json  0733.json  0876.json\n",
      "0018.txt   0161.txt   0304.txt\t 0447.txt   0590.txt   0733.txt   0876.txt\n",
      "0019.jpg   0162.jpg   0305.jpg\t 0448.jpg   0591.jpg   0734.jpg   0877.jpg\n",
      "0019.json  0162.json  0305.json  0448.json  0591.json  0734.json  0877.json\n",
      "0019.txt   0162.txt   0305.txt\t 0448.txt   0591.txt   0734.txt   0877.txt\n",
      "0020.jpg   0163.jpg   0306.jpg\t 0449.jpg   0592.jpg   0735.jpg   0878.jpg\n",
      "0020.json  0163.json  0306.json  0449.json  0592.json  0735.json  0878.json\n",
      "0020.txt   0163.txt   0306.txt\t 0449.txt   0592.txt   0735.txt   0878.txt\n",
      "0021.jpg   0164.jpg   0307.jpg\t 0450.jpg   0593.jpg   0736.jpg   0879.jpg\n",
      "0021.json  0164.json  0307.json  0450.json  0593.json  0736.json  0879.json\n",
      "0021.txt   0164.txt   0307.txt\t 0450.txt   0593.txt   0736.txt   0879.txt\n",
      "0022.jpg   0165.jpg   0308.jpg\t 0451.jpg   0594.jpg   0737.jpg   0880.jpg\n",
      "0022.json  0165.json  0308.json  0451.json  0594.json  0737.json  0880.json\n",
      "0022.txt   0165.txt   0308.txt\t 0451.txt   0594.txt   0737.txt   0880.txt\n",
      "0023.jpg   0166.jpg   0309.jpg\t 0452.jpg   0595.jpg   0738.jpg   0881.jpg\n",
      "0023.json  0166.json  0309.json  0452.json  0595.json  0738.json  0881.json\n",
      "0023.txt   0166.txt   0309.txt\t 0452.txt   0595.txt   0738.txt   0881.txt\n",
      "0024.jpg   0167.jpg   0310.jpg\t 0453.jpg   0596.jpg   0739.jpg   0882.jpg\n",
      "0024.json  0167.json  0310.json  0453.json  0596.json  0739.json  0882.json\n",
      "0024.txt   0167.txt   0310.txt\t 0453.txt   0596.txt   0739.txt   0882.txt\n",
      "0025.jpg   0168.jpg   0311.jpg\t 0454.jpg   0597.jpg   0740.jpg   0883.jpg\n",
      "0025.json  0168.json  0311.json  0454.json  0597.json  0740.json  0883.json\n",
      "0025.txt   0168.txt   0311.txt\t 0454.txt   0597.txt   0740.txt   0883.txt\n",
      "0026.jpg   0169.jpg   0312.jpg\t 0455.jpg   0598.jpg   0741.jpg   0884.jpg\n",
      "0026.json  0169.json  0312.json  0455.json  0598.json  0741.json  0884.json\n",
      "0026.txt   0169.txt   0312.txt\t 0455.txt   0598.txt   0741.txt   0884.txt\n",
      "0027.jpg   0170.jpg   0313.jpg\t 0456.jpg   0599.jpg   0742.jpg   0885.jpg\n",
      "0027.json  0170.json  0313.json  0456.json  0599.json  0742.json  0885.json\n",
      "0027.txt   0170.txt   0313.txt\t 0456.txt   0599.txt   0742.txt   0885.txt\n",
      "0028.jpg   0171.jpg   0314.jpg\t 0457.jpg   0600.jpg   0743.jpg   0886.jpg\n",
      "0028.json  0171.json  0314.json  0457.json  0600.json  0743.json  0886.json\n",
      "0028.txt   0171.txt   0314.txt\t 0457.txt   0600.txt   0743.txt   0886.txt\n",
      "0029.jpg   0172.jpg   0315.jpg\t 0458.jpg   0601.jpg   0744.jpg   0887.jpg\n",
      "0029.json  0172.json  0315.json  0458.json  0601.json  0744.json  0887.json\n",
      "0029.txt   0172.txt   0315.txt\t 0458.txt   0601.txt   0744.txt   0887.txt\n",
      "0030.jpg   0173.jpg   0316.jpg\t 0459.jpg   0602.jpg   0745.jpg   0888.jpg\n",
      "0030.json  0173.json  0316.json  0459.json  0602.json  0745.json  0888.json\n",
      "0030.txt   0173.txt   0316.txt\t 0459.txt   0602.txt   0745.txt   0888.txt\n",
      "0031.jpg   0174.jpg   0317.jpg\t 0460.jpg   0603.jpg   0746.jpg   0889.jpg\n",
      "0031.json  0174.json  0317.json  0460.json  0603.json  0746.json  0889.json\n",
      "0031.txt   0174.txt   0317.txt\t 0460.txt   0603.txt   0746.txt   0889.txt\n",
      "0032.jpg   0175.jpg   0318.jpg\t 0461.jpg   0604.jpg   0747.jpg   0890.jpg\n",
      "0032.json  0175.json  0318.json  0461.json  0604.json  0747.json  0890.json\n",
      "0032.txt   0175.txt   0318.txt\t 0461.txt   0604.txt   0747.txt   0890.txt\n",
      "0033.jpg   0176.jpg   0319.jpg\t 0462.jpg   0605.jpg   0748.jpg   0891.jpg\n",
      "0033.json  0176.json  0319.json  0462.json  0605.json  0748.json  0891.json\n",
      "0033.txt   0176.txt   0319.txt\t 0462.txt   0605.txt   0748.txt   0891.txt\n",
      "0034.jpg   0177.jpg   0320.jpg\t 0463.jpg   0606.jpg   0749.jpg   0892.jpg\n",
      "0034.json  0177.json  0320.json  0463.json  0606.json  0749.json  0892.json\n",
      "0034.txt   0177.txt   0320.txt\t 0463.txt   0606.txt   0749.txt   0892.txt\n",
      "0035.jpg   0178.jpg   0321.jpg\t 0464.jpg   0607.jpg   0750.jpg   0893.jpg\n",
      "0035.json  0178.json  0321.json  0464.json  0607.json  0750.json  0893.json\n",
      "0035.txt   0178.txt   0321.txt\t 0464.txt   0607.txt   0750.txt   0893.txt\n",
      "0036.jpg   0179.jpg   0322.jpg\t 0465.jpg   0608.jpg   0751.jpg   0894.jpg\n",
      "0036.json  0179.json  0322.json  0465.json  0608.json  0751.json  0894.json\n",
      "0036.txt   0179.txt   0322.txt\t 0465.txt   0608.txt   0751.txt   0894.txt\n",
      "0037.jpg   0180.jpg   0323.jpg\t 0466.jpg   0609.jpg   0752.jpg   0895.jpg\n",
      "0037.json  0180.json  0323.json  0466.json  0609.json  0752.json  0895.json\n",
      "0037.txt   0180.txt   0323.txt\t 0466.txt   0609.txt   0752.txt   0895.txt\n",
      "0038.jpg   0181.jpg   0324.jpg\t 0467.jpg   0610.jpg   0753.jpg   0896.jpg\n",
      "0038.json  0181.json  0324.json  0467.json  0610.json  0753.json  0896.json\n",
      "0038.txt   0181.txt   0324.txt\t 0467.txt   0610.txt   0753.txt   0896.txt\n",
      "0039.jpg   0182.jpg   0325.jpg\t 0468.jpg   0611.jpg   0754.jpg   0897.jpg\n",
      "0039.json  0182.json  0325.json  0468.json  0611.json  0754.json  0897.json\n",
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      "0127.json  0270.json  0413.json  0556.json  0699.json  0842.json  0985.json\n",
      "0127.txt   0270.txt   0413.txt\t 0556.txt   0699.txt   0842.txt   0985.txt\n",
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      "0128.txt   0271.txt   0414.txt\t 0557.txt   0700.txt   0843.txt   0986.txt\n",
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      "0131.txt   0274.txt   0417.txt\t 0560.txt   0703.txt   0846.txt   0989.txt\n",
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      "0132.json  0275.json  0418.json  0561.json  0704.json  0847.json  0990.json\n",
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      "0135.txt   0278.txt   0421.txt\t 0564.txt   0707.txt   0850.txt   0993.txt\n",
      "0136.jpg   0279.jpg   0422.jpg\t 0565.jpg   0708.jpg   0851.jpg   0994.jpg\n",
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      "0136.txt   0279.txt   0422.txt\t 0565.txt   0708.txt   0851.txt   0994.txt\n",
      "0137.jpg   0280.jpg   0423.jpg\t 0566.jpg   0709.jpg   0852.jpg   0995.jpg\n",
      "0137.json  0280.json  0423.json  0566.json  0709.json  0852.json  0995.json\n",
      "0137.txt   0280.txt   0423.txt\t 0566.txt   0709.txt   0852.txt   0995.txt\n",
      "0138.jpg   0281.jpg   0424.jpg\t 0567.jpg   0710.jpg   0853.jpg   0996.jpg\n",
      "0138.json  0281.json  0424.json  0567.json  0710.json  0853.json  0996.json\n",
      "0138.txt   0281.txt   0424.txt\t 0567.txt   0710.txt   0853.txt   0996.txt\n",
      "0139.jpg   0282.jpg   0425.jpg\t 0568.jpg   0711.jpg   0854.jpg   0997.jpg\n",
      "0139.json  0282.json  0425.json  0568.json  0711.json  0854.json  0997.json\n",
      "0139.txt   0282.txt   0425.txt\t 0568.txt   0711.txt   0854.txt   0997.txt\n",
      "0140.jpg   0283.jpg   0426.jpg\t 0569.jpg   0712.jpg   0855.jpg   0998.jpg\n",
      "0140.json  0283.json  0426.json  0569.json  0712.json  0855.json  0998.json\n",
      "0140.txt   0283.txt   0426.txt\t 0569.txt   0712.txt   0855.txt   0998.txt\n",
      "0141.jpg   0284.jpg   0427.jpg\t 0570.jpg   0713.jpg   0856.jpg   0999.jpg\n",
      "0141.json  0284.json  0427.json  0570.json  0713.json  0856.json  0999.json\n",
      "0141.txt   0284.txt   0427.txt\t 0570.txt   0713.txt   0856.txt   0999.txt\n",
      "0142.jpg   0285.jpg   0428.jpg\t 0571.jpg   0714.jpg   0857.jpg\n",
      "0142.json  0285.json  0428.json  0571.json  0714.json  0857.json\n",
      "0142.txt   0285.txt   0428.txt\t 0571.txt   0714.txt   0857.txt\n"
     ]
    }
   ],
   "source": [
    "!ls /tmp/myoutput/*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename='/tmp/myoutput/00000/0000.jpg') "
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "843de08df30066b821f0437d83317f7e657c9d58c210bb967a72474dd7dcb832"
  },
  "kernelspec": {
   "display_name": "Python 3.8.10 64-bit ('.env': venv)",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
